PhD position on eddy covariance and wavelet analysis
INRAE - French National Research Institute for Agriculture, Food, and Environment
The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a major player in research and innovation. It is a community of 12,000 people with 272 research, experimental research, and support units located in 18 regional centres throughout France. Internationally, INRAE is among the top research organisations in the agricultural and food sciences, plant and animal sciences, as well as in ecology and environmental science. It is the world’s leading research organisation specialising in agriculture, food and the environment. INRAE’s goal is to be a key player in the transitions necessary to address major global challenges. Faced with a growing world population, climate change, resource scarcity, and declining biodiversity, the Institute has a major role to play in building solutions and supporting the necessary acceleration of agricultural, food and environmental transitions.
The Silva Joint Research Unit brings together people from AgroParisTech, INRAE, and the Université de Lorraine to conduct multidisciplinary research on wood, trees and forest ecosystems. It is the result of the merge of the joint research units « Forest Ecology and Ecophysiology » [EEF] and « Laboratory of Wood Forest Resource Studies » [LERFoB] in January 2018. The main scientific goal of the UMR Silva is to develop pure and applied research to answer questions of society, including forest managers, about (1) the role and the future of forest ecosystems in the context of global changes, including climate change, and (2) the future of the timber industry, particularly in the Grand – Est region for which it is of major economic importance.
Homepage: https://silva.nancy.hub.inrae.fr/
Biogeosciences (BG)
Hydrological Sciences (HS)
Land vegetation is currently under unprecedented pressure due to climate change. A better understanding of how plants respond to environmental stresses, such as heat waves and droughts, is essential for designing effective mitigation strategies.
The eddy covariance method is now the leading method for measuring greenhouse gas exchanges between ecosystems and the atmosphere. It provides continuous, direct data that is widely used for studies on droughts, atmospheric inversions, satellite validation, etc. The method makes it possible to estimate the carbon sink of soils and plants, resulting from the balance between carbon absorbed by photosynthesis (gross primary productivity, GPP) and carbon emitted by ecosystem respiration (RE).
The future of terrestrial carbon sinks will depend on the evolution of these carbon fluxes. Understanding how photosynthesis and respiration respond to extreme events (heat, drought) is therefore essential to guide the transition to a low-carbon economy and help ecosystems adapt.
We have recently developed a method based on wavelet analysis to estimate ecosystem fluxes even under non-stationary conditions (Destouet et al. 2024). In addition, another study used wavelet analysis to estimate photosynthesis and respiration from the eddy covariance raw data (Coimbra et al. 2023).
Objective: The aim of this thesis is to combine and improve these approaches in order to offer a comprehensive alternative to conventional data processing, including the partitioning of CO2 fluxes into photosynthesis and respiration. The method will be tested on data from the European research infrastructure ICOS (www.icos-cp.eu), which brings together more than one hundred sites equipped with instruments for monitoring carbon fluxes in ecosystems and covering a wide variety of ecosystems and climatic conditions. This thesis will contribute to a better understanding of how agricultural and forest ecosystems function by providing more reliable observations of the impact of climate on soils and plants. These results will be useful for research on water resources, extreme events, climate modelling and long-term monitoring of greenhouse gas emissions by terrestrial and ocean ecosystems, and by cities.
Profile: We are seeking a motivated candidate who is eager to work in an interdisciplinary setting at the intersection of signal processing, fluid mechanics, and ecophysiology. They should have strong computer skills, an aptitude for mathematics, have interest in research related to climate change, and an affinity to work with international partners.
Time and Place: The thesis will take place for three years at the UMR Silva on the campus of INRAE near Nancy (54280 Champenoux) from autumn 2025 onwards, with frequent visits to UMR Ecosys in Paris-Saclay.
Contact the supervisors: matthias.cuntz@inrae.fr and pedro-henrique.herig-coimbra@inrae.fr
Detailed information on the PhD thesis can be found here: https://www.macu.de/extra/PhD_Wavelet_long_en.pdf
Send to the PhD superisors a cover letter, a CV, the transcript of grades of the master (or of the 3 years of engineering school), a contact information of an academic reference, as well as a résumé (300 words) of the master topic (or of the end-of-study internship).